Genetic diversity analysis of some Bangladeshi aromatic rice (Oryza sativa L.) using simple sequence repeat markers (SSRM)

In order to germplasm management, conservation, parental identification and proper utilization of aromatic rice germplasm of Bangladesh genetic diversity assessment and molecular characterization is necessary. We used ten microsatellite markers across twenty aromatic rice landraces along with four improved varieties to discriminate and characterize among them. The number of alleles per locus ranged from 2 to 8, with an average of 4.30 alleles across 10 loci. A total of 43 polymorphic alleles were detected. The values of Polymorphic information content (PIC) ranged from 0.217 to 0.835 (average 0.495) which indicate high genetic diversity among the studied aromatic rice genotypes. It was concluded by the PIC value of RM5339 that it might be the finest marker for diversity estimation and characterize of these aromatic rice genotypes, followed by RM334, RM414 and RM28502 markers. The UPGMA cluster dendrogram constructed in this study identified seven clusters with a correlation coefficient 0.874. Molecular characterization of aromatic rice landraces of Bangladesh exhibited large variations among the genotypes. Five rice genotypes namely BRRI dhan38, BRRI dhan50, Bashmoti safed, Malaysira, Khas-kani showed highest genetic dissimilarity among the studied rice genotypes. The findings of this study would be useful for background selection in backcross breeding programs for aromatic rice improvement as well as identification of genetically distant and genetically close accessions for maintenance and conservation

In vitro response and effect of gamma irradiation on four local indica rice varieties

In vitro response of four local Indica rice cultivars viz. Sadamota, Kachamota, Moulata and Dudhkalam was evaluated. The aim of this study is to develop an efficient protocol for callus induction, plant regeneration and to observe the effect of gamma radiation on plant regeneration for creating possible genetic variability. In Different concentration of 2,4-D and growth regulators were supplemented with MS medium (Murashige and Skoog’s) to observe their callus induction frequency using mature embryo as explant. Among the cutivars, the highest primary callus (92.55%) as well as embryogenic callus induction (56.26%) was showed in sadamota at 3.0 mgl-1 2,4-D and 10 mgl-1 kinetin under dark condition. Twenty one days old embryogenic calli were exposed to 0, 2, 4 and 6 Gy of gamma rays and transferred to regeneration medium. Both callus growth and regeneration capacity were found to be decreased with increasing level of exposure to gamma rays. The doses of 4 Gy of gamma radiation were found to be the 50% inhibition dose for callus growth and plant regeneration in sadamota and kachamota, repectively whereas the 50% inhibition dose for moulata and dudhkalam at 2 Gy. This results indicate that sentivity of gamma radiation on rice callus depends on genotype of a genus

Gamma Radiated Wheat for Combating Devastating Blast Disease (Magnaporthe Oryzae Triticum) In Bangladesh

Wheat is a global food security crop, providing 20 percent of protein and calories consumed worldwide and up to 50 percent in developing countries. It is the second most important cereal next to rice in Bangladesh and playing an important role in attaining food security. But wheat is very susceptible to diseases that often place major biological constraints on production. In 2016, a new wheat disease called “blast” was identified by wheat scientists for the first time in Bangladesh. Wheat blast disease caused by Magnaporthe oryzae triticum is causing enormous yield loss worldwide. At present, control of blast disease is a great challenge due to frequently introduction of new races of the pathogen. The present investigation focused on screening M2 population of gamma radiated wheat where four doses of radiations viz. 150 Gy, 200 Gy, 250 Gy, and 300 Gy were applied to the seeds of three wheat varieties viz. BARI Gom-25, BARI Gom-29 and BARI Gom-30 from a Cobalt 60 source (Gamma Chamber 5000). The irradiated seeds were sown in farmers’ fields of a wheat blast disease-prone area Chandbil, Meherpur Sadar. All the doses of irradiation showed a significant effect on incidence and severity of wheat blast disease in all three varieties. Among the treatments 200 Gy and 250 Gy reduced the disease effectively. Molecular detection of Magnaporthe oryzae triticum was also done using specific primer. The size of the band (350 bp) confirms the infection of M2 families by Magnaporthe oryzae triticum. Development of wheat blast resistant variety through irradiation could be a potential substitute to replace the available chemical control methods and it is described as eco-friendly, sustainable and nonhazardous strategy to reduce wheat yield loss due to blast disease

Expression and subcellular localization of antiporter regulating protein OsARP in rice induced by submergence, salt and drought stresses

We examined the expression and subcellular localization of antiporter regulating protein OsARP in a submergence tolerant rice (Oryza sativa L.) cultivar FR13A. In the public databases, this protein was designated as putative Os02g0465900 protein. The cDNA containing the full-length sequence of OsARP gene was present in Gene Bank Accession no. AK071205 and this encoded 216 amino acids which had molecular mass of 25 kD. The OsARP gene was first expressed into E. coli and antibody was produced by using purified recombinant protein. The expression of OsARP protein was detected under submergence, salt and drought stresses. This protein was widely expressed in roots, shoots and leaves of rice under salt stress. To get an insight into the functional role of OsARP protein, subcellular localization was done using cell fractionation of rice leaves. Immuno-blotting of 3-day submergence rice leaves cell fractions detected the presence of OsARP protein in plasma-membrane fraction only. This indicates that OsARP is a membrane bound protein of rice which is expressed under submergence, salt and drought stresses.Key words: Drought, antiporter regulating protein, immuno-localization, rice, salinity, submergence

Combining Machine Learning Classifiers for Stock Trading with Effective Feature Extraction

The unpredictability and volatility of the stock market render it challenging to make a substantial profit using any generalized scheme. This paper intends to discuss our machine learning model, which can make a significant amount of profit in the US stock market by performing live trading in the Quantopian platform while using resources free of cost. Our top approach was to use ensemble learning with four classifiers: Gaussian Naive Bayes, Decision Tree, Logistic Regression with L1 regularization and Stochastic Gradient Descent, to decide whether to go long or short on a particular stock. Our best model performed daily trade between July 2011 and January 2019, generating 54.35% profit. Finally, our work showcased that mixtures of weighted classifiers perform better than any individual predictor about making trading decisions in the stock market

Application and Analysis of Retail Inventory Using Data Mining Techniques

Data mining is one of the most essential tools for gathering information from different datasets in almost all recent industries. In this 21st-century, data mining gained attention because of its significance in decision making, and it has become a key component in various industries such as retail. Inventory management requires pre-planned goals and attention to detail, and prioritizing items that require less attention can be a waste of time and resources. Learning indications about customers2019; shopping patterns by showing associations among various provides significant value in managing retail inventory. In the present research paper, popular data mining techniques have been applied and analyzed for multi-item inventory management in retail sales stores to show how data mining techniques can optimize and organize the retail inventory

Designing and developing a vision-based system to investigate the emotional effects of news on short sleep at noon: an experimental case study

Background: Sleep is a critical factor in maintaining good health, and its impact on various diseases has been recognized by scientists. Understanding sleep patterns and quality is crucial for investigating sleep-related disorders and their potential links to health conditions. The development of non-intrusive and contactless methods for analyzing sleep data is essential for accurate diagnosis and treatment. Methods: A novel system called the sleep visual analyzer (VSleep) was designed to analyze sleep movements and generate reports based on changes in body position angles. The system utilized camera data without requiring any physical contact with the body. A Python graphical user interface (GUI) section was developed to analyze body movements during sleep and present the data in an Excel format. To evaluate the effectiveness of the VSleep system, a case study was conducted. The participants' movements during daytime naps were recorded. The study also examined the impact of different types of news (positive, neutral, and negative) on sleep patterns. Results: The system successfully detected and recorded various angles formed by participants' bodies, providing detailed information about their sleep patterns. The results revealed distinct effects based on the news category, highlighting the potential impact of external factors on sleep quality and behaviors. Conclusions: The sleep visual analyzer (VSleep) demonstrated its efficacy in analyzing sleep-related data without the need for accessories. The VSleep system holds great potential for diagnosing and investigating sleep-related disorders. The proposed system is affordable, easy to use, portable, and a mobile application can be developed to perform the experiment and prepare the results

Social Innovation and the Financial Risk of EMNCs - The Contingent Role of Institutional Legitimacy

This paper examines the influence of social innovation on financial risk of emerging economy multinational corporations (EMNCs). Traditionally, research has focussed on Western MNCs’ and their financial performance implications. However, the growing involvement of EMNCs in social innovation—albeit in environments characterized by institutional voids—and its effects on financial risk necessitate an in-depth examination. Drawing on stakeholder theory, we explored how EMNCs balance their social innovation initiatives with financial risks. To this end, we first examine how social innovation reduces the financial risk of EMNCs. Second, we examine the association between excessive social innovation and EMNCs’ financial risk. In addition, borrowing insights from institutional theory, we assess the role played by institutional legitimacy in this process, acknowledging institutional legitimacy’s potential to mitigate the financial risks associated with social innovation in emerging economies. We test our hypotheses based on data drawn from 90 EMNCs in 14 emerging economies, applying a panel regression model with robust standard errors and a rigorous robustness propensity score matching test. Our findings show that social innovation reduces EMNC financial risk, and challenge the assertions made regarding the potential negative implications of excessive social innovation on financial risk. Our results also demonstrate the intricate moderating effects of institutional legitimacy in balancing social innovation, excessive social innovation, and EMNC financial risk. Finally, we proffer critical implications for managers and policymakers in emerging economies